Search for tag: "network"
Allen-Blanchette, Christine -"Learning the Rules of Self-Organization with Behavior-Inspired Neural Networks"AI for Accelerating Invention, a new Princeton AI Lab initiative, integrates artificial intelligence into engineering research, developing new technologies and tools to accelerate the process of…
From Broadcast Broadcast Center Staff
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ReMatch+ Intern - Michel LiaoThrough Glasses: A Multi-Layer Transparent Segmentation Network Advised by: Jia Deng, Computer Science Erich Liang, Computer Science
From our Undergraduate Research
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OURSIP Intern – Daniel TanNetworked Interactions in Biomolecular Condensates Formed by Disordered Proteins Advised by:Prof. Jerelle A. Joseph, CBE Dr. Dilimulati "Morat" Aierken, CBE
From our Undergraduate Research
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Thinking About Pain, the Brain, and You, Toru Obunge, UG '24 (F39094D0)There is growing research into psychological treatments for pain conditions, such as music therapy, cognitive-behavioural therapy (CBT), and mindfulness-based interventions. However, a unifying…
From Research Princeton Research Day
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Analyzing How Neural Networks Manipulate the Shape of Data, Reuel Williams, UG '24 (9C22A282)Understanding the mathematical shape of data that neural networks learn from can provide valuable insights into their inner workings. In my senior thesis, I delve into this concept using a…
From Research Princeton Research Day
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Challenging the Party's Lead: Reframing Chinese Law & its Influence Upon American Data Privacy, Zoe San Martin, UG '24 (64FAF405)Over the last decade, the People’s Republic of China (PRC) and its data privacy regime have drawn national security concern. Adding onto the critique of Chinese authoritarianism, policy…
From Research Princeton Research Day
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Quasiclassical Trajectory Calculations of Rate Constants Using an Ab-initio Trained Machine Learning Force Field (aML-MD), Zhiyu Shi, GS (7ACD870A)Machine learning (ML) provides a great opportunity for the construction of models with improved accuracy for classical molecular dynamics (MD). However, the accuracy of a machine learning trained…
From Research Princeton Research Day
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